economic information (e.g., GDP, interest rates, inflation, etc.), funda-mental factors refer to observable asset attributes (e.g., industry, marketcapitalization, price to earnings ratio, etc.), statistical factors are the leastintuitive, because they are unobservable factors. The factor we explore inthis paper is a statistical factor derived from Principal ComponentAnalysis used for explanatory purposes.Additionally, in this research, the Merton structural approach is usedto provide a link between equity and debt instruments. Merton intro-duced the structural model (1974) and its extension the ContingentClaim Approach (CCA) to understand the sectors of an economy asinterconnected portfolios1(Merton et al., 2013), and extend this phi-losophy to understand the world economy as a single portfolio of assets,liabilities and guarantees. The CCA framework applies option-pricingtheory to the valuation of assets. This provides a link between equityand credit risk (Gray et al., 2007) being the credit risk the possibility of aloss resulting from a company's or sovereign's default. The growinginterdependence among local economies due to globalization and spe-cifically cross-borderfinancial activity presents the theoretical justifica-tion for cross-country and cross-market linkages. Shocks are transmittedthrough the economies' real sector or through otherfinancial channels(Bratis et al., 2015).Following these insights, this paper explores how relations proved bytwo mainstreamfinance theories work at the intersection: Mertonstructural approach and international asset pricing models.Our contribution is twofold: First,finding a global factor that iscommon to several markets and regions is a rare exercise. However, thisunderlying factor, which span assets worldwide, if found, is very usefulfrom the point of view of investors. On the one hand, because it can serveas benchmark for evaluating performance of active investments. On theother hand, because, asPukthuanthong and Roll (2009)andCotter et al.(2018)have explained, it can be interpreted as a global integrationmeasure across markets based on the explanatory power of a multi-factormodel applied to different countries. Being an indicator of marketsintegration, the risk factor can also be used as a guide for investments (oralternatively for risk diversification). Insights into complexities of factorbehavior can help investors to better anticipate how their portfoliosmight perform in the future (FTSE Russell, 2019).Second, we use a novel approach to estimate a common underlyingrisk factor that underlies the global credit and equity markets. The paperseeks to provide an initial framework to help investors with diversifica-tion' strategies, by using the information provided in debt and equityinstruments. To the extent of our knowledge, this is thefirst paper toinclude the information in both markets to this end. As explained byShahzad et al. (2018)understanding the dynamics of the co-movement ofboth markets at different horizons as well as primary determinantsmaybe useful for investors and portfolio managers in order to makebetter asset allocation, portfolio rebalancing and risk management de-cisions. Also, industry papers have long recognized these in-terdependencies: some examples are the papers byKapadia and Sinder(2017),Invesco (2019).2We consider the information embedded in the prices of three differentfinancial instruments which account for the credit and equity market of aworldwide sample: Sovereign Credit Default Swaps (SCDS hereafter),Corporate Credit Default Swaps (CCDS) and equities, fromfinancial andnon-financial companies from 14 countries. We study 135 institutions:121 companies,financials (54) and non-financials (67) across 14different countries, through the threefinancial instruments (SCDS, CCDSand equities) for a long period of 9 years (2007–2015).We quantify this interdependence among markets and regions byusing Principal Component Analysis (PCA). For this reason, our factor is astatistical factor with no direct connection to any macroeconomic vari-able. The underlying risk factor uncovered should be understood as asystematic factor related to common economic forces, which cannot bediversified away. Its meaning also matches the common systematiccomponent found byCollin-Dufresne et al. (2001)when studying CCDSsandLongstaff et al. (2011)in SCDS, among others.3The paper explores the main features of this systematic risk factor,studies its consistency, its geographical structure and its evolution alongthe period studied. As robustness check we validate its meaningfulnessrelating it to the VIX index. The VIX is the Chicago Board Options Ex-change (CBOE) Volatility Index. The VIX is widely recognized as an in-dicator of investors' risk aversion andfinancial markets' inherentuncertainty, for this reason it affects asset prices (Pukthuanthong andRoll, 2009;Song and Xiu, 2016;Pan and Singleton, 2008). Accordingly, itseems reasonable to believe that changes in the VIX may induce revisionsin investors' allocations and risk management strategies affecting thecredit and stock market link (Shahzad et al., 2018). As inLongstaff et al.(2011)we relate our common risk factor to the evolution of the VIXindex.The rest of the paper is structured as follows. Next, we explain thetheoretical framework. In section3we present the data and methodol-ogy. Then, in section4, we, describe and discuss the results. Conclusionscan be found at the end of the paper.2. Theory and evidenceThe paper's goal is to extract a common risk factor underlying globalcredit and equity markets. For this reason, we present our deductivereasoning to link the two markets together. The approach followed relieson both theories: Merton structural approach and international assetpricing models.Several papers support the rational long run interdependencies be-tween the credit and market risk: by means of the search for long runequilibrium (e.g.,Carr and Wu, 2010;Baele et al., 2010;Figuer-ola-Ferretti and Paraskevopoulos, 2013;Mateev and Marinova, 2019),common fundamentals (e.g.,Bystr€om, 2008,2018;Forte and Lovreta,2015) or causality links (e.g.,Fung et al., 2008;Forte and Pena, 2009;Shahzad et al., 2017).All corporate issuers have some positive probability of default, whichchanges with thefirm's stock price and thus its leverage.Merton (1974)was thefirst to demonstrate that afirm's default option could be modeledwith theBlack and Scholes (1973)methodology. The basic Merton modelhas been extended in many ways, yielding models that have considerableexplanatory power (for a good review seeSundaresan, 2013).The right-hand side of a company' Balance Sheet (the liabilities) canbe thought of as a claim against its left-hand side (the assets). Liabilitiesare all linked to the same assets, and there are different rules to assignthese assets under different conditions. This implies that debt and equityshould move together. Equity investors as well as bondholders and CDSbuyers should consider default probabilities, recovery rates and relevantaccounting ratios. Thesefinancial instruments are tied to the same un-derlying asset value. This links the prices of equity and debt.These aftermaths corroborate evidence found byForte and Lovreta(2015)in relation to the stock market's informational dominance versusthe CDS market, particularly in times of crisis. It also holds with the1CCA refers to the Corporate Structural Model or Merton Model application tofinancial institutions and sovereigns.2Industry papers have long recognized the importance offinding diversifyingassets for equity risks, these diversifying assets should have insurance propertiesand show negative correlations with equities. Fixed Income, Commodities,Currencies, Real State, Timberland, have long been considered diversifier’investments.3The risk systematic risk factor studied does not necessarily have afinancialroot, and in this sense, it is not a systemic risk. Along the literature wefind“interconnectedness”,“systemic risk”and“macro-financial risks”as synony-mous (e.g.,Yellen, 2013;Billio et al., 2012;Merton et al., 2013;Longstaff et al.,2011, etc.).T. Corzo et al.Heliyon 6 (2020) e039802